Sarawan Wongsa

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This paper presents a method for identifying the optimum structure of Wiener model with piecewise linearisation. The number of piecewise linear functions for estimating the static nonlinear and the maximum lag of the linear dynamic part of the Wiener model are selected by cross-validation based approach. The maximum lag and the number of partitions are(More)
Metabolic flux analysis is important for metabolic system regulation and intracellular pathway identification. A popular approach for intracellular flux estimation involves using ^{13}{\rm C} tracer experiments to label states that can be measured by nuclear magnetic resonance spectrometry or gas chromatography mass spectrometry. However, the bilinear(More)
Metabolic fluxes have been regarded as an important quantity for metabolic engineering as they reveal cause-effect relationships between genetic modifications and resulting changes in metabolic activity and are used as a prerequisite for the design of optimal whole cell biocatalysts. The intracellular fluxes must be estimated due to the inability to measure(More)
This paper presents the development of control technique for an internal combustion engine which controls fuel injections for various gasoline/ethanol mixtures. Yamaha motorcycle, Spark 135i, is tested to find the injection timing for E0, E20, E85 and E100, respectivelty. The experiments are conducted with a speed upto 8000 rpm and working load between 0(More)
The data recorded in industry for rotating machine health monitoring are often a large number and unlabelled. It is impractical to label these data manually. Traditionally unsupervised algorithms have been applied to address this challenge. In the situation where relevant features are included or when the features are not selected properly, it could lead to(More)
This paper presents an algorithm for quantifying valve stiction in control loop based on linear decrease inertia weight particle swarm optimisation. The amount of stiction present in the valve is estimated by identifying parameters of Kano model which is a two-parameter data-driven stiction modelling based on the parallelogram of MV-PV phase plot.(More)
Partial least squares (PLS) is a potential data-driven technique to deal with a huge number of measured variables and complex relationship. It could be used for process monitoring even for chemical processes that have nonlinear dynamic properties. In this paper PLS is applied to detect two fault types which occurred in real Acid Gas Removal Units (AGRU) of(More)
This paper proposes a new early stopping algorithm for improving processing time of nonnegative garrote (NNG)-artificial neural network (ANN) variable selection method which has been used for reducing model complexity in soft sensor application. The performance of the proposed method is compared with conventional NNG-ANN variable selection algorithm. The(More)